Big Data Economics
This module will focus on advanced Big Data methods and their applications in various economics problems. Topics of the module include:
- nonlinear models
- tree-based models
- support vector machines
- unsupervised learning and applications in international trade
- household finance
- macro forecasting
- labor economics
- text analysis
Machine Learning for Economics
This module is intended as an introduction of the methodology and implementation of machine learning methods used widely in economic analysis; the module provides an introduction to the analysis of large datasets, with more up to date Big Data methods introduced later as natural developments. Topics will include:
- an introduction to statistical computing in R
- generating random variables and random processes
- Monte Carlo integration and variance reduction; high performance computing
- multivariate linear regression
- resampling methods
- linear model selection and regularization
This module covers:
- modern techniques of microeconomic theory
- foundations and applications of game theory
- information economics
This module will cover analytical and theoretical issues in macroeconomics including:
- modelling aggregate variables under adaptive and rational expectations
- modelling with imperfect competition
- constructing overlapping generations models
- price inertia
This module teaches the core techniques of econometric theory, including:
- detailed analysis of the multiple linear regression model
- large sample theory
- asymptotic testing procedures
- non-linear techniques
- mis-specification testing
Economic Data Analysis
This module provides you with 'hands on' training in the use, presentation and interpretation of economic data, including time series, cross-section and panel data. It comprises of:
- an introduction to basic principles of economic data analysis
- descriptive statistics
- hypothesis testing
- simple and multiple regression
- introduction to panel data
- introduction to dynamic modelling
- time series models
The module will include a series of practical classes using econometrics software packages.
Economic Research Methodology
This module covers the following:
- A review of perspectives on the principles and philosophical foundations of economic enquiry
- The construction and evaluation of theories and research programmes
- The role of models and concepts of rationality in economics
- Alternative empirical methods
- Professional practice
Advanced Macroeconomic Methods
This module covers the theory for the solution and estimation of dynamic stochastic models that are widely used in all fields of macroeconomics. The module is structured in a way such that you will be exposed both to theory and the practical implementation of the methods taught.
It covers topics from approximation methods for stochastic non-linear macroeconomic models, such as linear and higher-order Taylor approximation as well as dynamic programming techniques. It also exposes students to the empirical evaluation of these models ranging from calibration to classical and Bayesian estimation methods.
The module applies the techniques to contemporary general equilibrium macroeconomic models designed for positive and policy analysis such as the New Keynesian model but also models that are designed to explain partial equilibrium behaviour such as consumer saving and industry investment.
This module covers the following:
- International linkages in economics as a result of exchange rate movements, capital movements and spillovers
- Factors which determine the level of the exchange rate and trade effects
- International effects of monetary and fiscal policies
Monetary Theory and Practice
This module covers monetary aspects of advanced macroeconomics and is suitable for students of mainstream economics, finance and international economics. It focuses on the theory and practice of central banking, monetary policy and control.
It covers concepts such as time inconsistency, the problem of inflation bias with solutions, credibility, transparency and accountability of monetary institutions, inflation targeting and price stability, the choice of instruments for monetary policy and their control, and finally monetary transmission. It combines some theory with evidence and practice.
Time Series Econometrics
The module covers fundamental properties of time series and various classes of stochastic processes. Issues in estimation and forecasting of time series models; concepts of contemporary interest to time series econometricians are also covered.
Financial and Macroeconometrics
The module extends the coverage of advanced econometric modelling techniques and considers their application through the study of selected topics in finance and macroeconomics, developing familiarity and critical awareness of empirical research in these areas.
It covers techniques for the analysis of stationary ARMA processes, Vector Autoregressions (VARs), linear regression models, linear systems of simultaneous equations, cointegration, long-run structural VARs, forecasting, and models of changing volatility. The selected topics include the econometric analysis of business cycle fluctuations, wage, price and (un)employment determination, portfolio choice and stock market returns.
The module considers modern econometric techniques for modelling microeconomic data. It covers four broad econometric techniques:
- Robust standard errors and applications
- Discrete choices model
- Microeconometric policy evaluation methods for observational studies
- Instrumental variables and GMM estimation
Economics of Corporate Finance
This module offers an introduction to the economics of corporate finance. It is designed to provide you with the basic theoretical background in this area that is necessary for any applied work. Emphasis is placed on the analysis of simple models and their applications.
The module covers a variety of topics with substantial time devoted for covering issues directly related to the financial needs of firms, such as capital structure, credit rationing and corporate governance.
The module also examines the role of financial intermediaries analysing bank failures and, consequently, the scope for banking regulations. The last part of the module looks closely at the relationship between the financial sector and the real economy thus offering the background for any applied work related to the link between financial development and economic fluctuations.
Economics of Household Finance
This module covers the central issues in the economics of household finance. Increasingly economists are interested in the decisions of consumers as well as the decisions of firms.
Household finance is the study of the behaviour of individuals and households in financial markets including those for secured (for example, mortgage) and unsecured (for example, credit card) lending and related economic models of consumption smoothing, liquidity constraints and household behaviour.
The module begins with the central topic of consumption smoothing, focusing on the role of credit markets and income risk in household behaviour. Later topics include financial literacy, self-control, mortgage market design, stock market participation and the regulation of consumer credit markets.
The module content includes come theoretical material but is mostly applied, with a focus on how large-scale individual level proprietary and survey datasets can be used to understand household financial behaviour.